Recently, the influx of IoT devices has increased the need for security and personal information protection of devices and users of the devices. However, current security solutions are not scalable and difficult to protect against attacks on new routes. Therefore, to solve the problem of security and personal information protection, it is necessary to develop an overall security solution considering context information.
Prior to integrating navigation into security, we would like to introduce a human navigation method. The human navigation method in indoor and outdoor environments can ultimately reduce the estimate of distance and direction for one or several known reference points.
For example, when a person is driving a car, the person can use a device in a state of recognizing a distance and direction of another car in front, side, or rear, even if the person does not recognize all the distances and directions of the surrounding cars.
To this end, a user periodically estimates changes in displacement and orientation and adds the estimated displacement and direction to a distance and direction in relation to a reference point for calculating a user location and direction.
All positioning and navigation methods are based on a dead-reckoning or landmark-based exploration method. In this case, the dead-reckoning method, also known as path integration, is based on a single reference point throughout the exploration.
Here, dead-reckoning records and integrates changes in position or speed. To calculate the position, a new measurement value is added to the value of a previous position.
On the other hand, unlike dead-reckoning, a landmark-based exploration method known as position fixation is based on several identifiable reference points (landmarks). Here, a user mutually exchanges a space between the reference points while tracking a relative position of the landmark via navigation. This technology requires a physical or cognitive map for an environment.
Moreover, navigation and positioning systems can also be divided into three categories, i.e., a navigation system, a location system and an integrated navigation system.
The location system can estimate a location only. Yet, the navigation system can automatically estimate a speed and location. Moreover, the integrated navigation system known as a hybrid location system can estimate a location and speed using two or more technologies.
Since all navigation systems are basically capable of location measurements, a location measuring method may include dead-reckoning, direct-sensing, triangulation and pattern recognition, which can be realized by non-limited methods.
Namely, the location measuring method can be classified into dead-reckoning, direct-sensing, triangulation and pattern recognition. The aforementioned 4 kinds of technologies shall be described in the following.
Hereinafter, a term ‘context’ is a broad term, non-limited by location information and/or directions.
Hereinafter, position and location are interchangeable even if expressed differently. Position is expressed qualitatively while location is expressed quantitatively. In other words, positioning and localization can also be interpreted in the same manner as above.
Dead-Reckoning
Dead-reckoning determines and cumulatively calculates a user's location by measuring a location, a speed or changes of a location and speed. Here, the cumulative calculation is to calculate a current location in a manner that a change of a location value is combined with a previous location value. For example, a distance and speed can be respectively measured using a walk speedometer or an odometer.
Moreover, in case of an aviation or marine application, devices such as radars, sonars and cameras can be used. Here, azimuth, pitch and roll measurements can be obtained using at least one of an accelerometer, a gyroscope and a magnetometer. A quality of such a sensor may have a noticeable level difference in costs depending on an application. For example, in case of an aviation application, a cost of such a sensor is estimated as several thousand dollars. Yet, in case of a mobile application, a cost amounts to 1 dollar or less only. Moreover, a complete 3D dead-reckoning navigation system is Inertial Navigation System (INS).
Dead-reckoning has two disadvantages different from those of INS. The first disadvantage is that location should be frequently reset using GPS, radio frequencies and the like. Second, due to the recursive nature of the dead-reckoning location, errors tend to accumulate over time. On the other hand, dead-reckoning also has many advantages, including reduced installation costs, continuous operation and the like.
Direct Detection
A location measurement method based on direct detection estimates a location by accessing a close equation of an identifier or tag installed in the environment. As a result, when a signal is received, a receiver location is assumed to be a transmitter location. That is, if a user tag gets closer to a landmark, a landmark location is assumed as a user's location.
Moreover, information on a location and user may be saved to a tag itself or found from a database. Here, database information may be located in a user device in advance or use a landmark database created by a navigation system using a technique called Simultaneous Localization And Mapping (SLAM).
Moreover, environment characteristics can be measured using other sensors such as a camera, a laser scanner, a radar, a sonar and the like. In this case, user direction estimation is computed by consecutive tag detections according to relative location changes.
A tag used for identification is based on 5 techniques, i.e., Radio Frequency Identification (RFID), Bluetooth Beacon, barcode, Infrared Ray (IR), and Ultrasound Identification (USID).
Direct detection has an advantage that location measurement can be performed quickly and accurately with low costs but disadvantages such as installation costs of a transmitter, a short range (cf. a wide range requires more power), and interference from natural lights, artificial illumination and the like.
Triangulation
Navigation techniques based on triangular measurements require at least three known reference points to estimate a user location. Traditional triangulation techniques are the lateration method and the angulation method, also referred to as location measurements by distance selection and angle selection. Lateration is a method of calculating a location by measuring a distance from three or more reference points that know the absolute locations to a corresponding sensor node, i.e., based on a distance between a user and at least one of the three reference points. Angulation is a method of finding a distance by measuring a relative angle from at least one of three reference points.
Lateration-based navigation is used in Global Positioning System (GPS). GPS can use signals measured from satellites to estimate the range between a user and a satellite. Each range measurement estimates the zone of the sphere around the reference point. The intersection of these two spheres defines the position line of the circle and three spheres have only two points of intersection. Therefore, three or more distance measurements are required to achieve one position. The navigation according to an angle is used for commercial and military applications where multiple antenna arrays are used to estimate the angle of introduction. The introduction angle (introduction direction) estimates the angle at which the signal reaches the receiving signal, thereby indicating a location of a mobile station. Then, a position is estimated using a geometric relationship. That is, at least three receivers are required for position measurement in three dimensions.
Wireless Local Area Networks (WLANs) and Cell Towers (cell-towers) may be used instead of GPS for location measurements when GPS signals are not available. The former uses the signal strength of each mobile phone tower to triangulate a position using information on a cell tower position, while the latter uses a provided signal strength of each station to triangulate the position of a radio base station. Both of the techniques have the disadvantage that they are less accurate than GPS.
Pattern Recognition
In pattern recognition based on location measurement, massive sensor data are obtained from different environmental locations and then combined with a context map. During navigation, a signal recognized by a user device is compared with previously collected sensor data and a location is inferred by an environment-combined map. Other techniques use different sensors.
For example, a camera is used to provide an image to a computer and a signal detected through the camera corresponds to an image. While a user explores an environment, a captured image can be compared with an image database of user locations to determine the user's location. The disadvantage of this approach is large memory and much computation that are required for a matching process. Moreover, multiple training steps are required for signal distribution or fingerprint recognition. As a result, a map can be generated by measuring the strength of signals received at different locations and saving the signal strength values to a database.
During navigation, a received signal strength or distribution over time is measured and compared with the map to find the closest match. For example, Wireless Local Area Networks (WLANs) is an example of a signal distribution location measurement.
Security through public key infrastructure (PKI) based schemas is now widespread. However, the disadvantages of PKI are well known and there are several solutions that are not based on PKI. One of them is an identity-based and certificate-less public key encryption schema.
In the following, the present specification proposes a context-aware ID based encryption solution using a non-PKI-based scheme.